Sustainable engineering challenges towards Industry 4.0: A comprehensive review

This article reviews Industry 4.0, its emerging phase, implementation, challenges, benefits, etc. It combines various fields where it has any influence and leaves some changes and where it requires some adaptation. Papers from the last 4 years are taken and analyzed, what is written about this topic in various countries with different backgrounds and economic development. Industry 4.0 affects the production environment by introducing new technologies which require a better-educated workforce so it affects education and requires some changes in curricula and ways of teaching. It brings new challenges and asks for a new approach from management to be able to handle fast and big changes in the business environment and to implement such innovation in production effectively

Fatores críticos de sucesso na gestão do conhecimento: um estudo de caso baseado na implementação de uma academia do conhecimento

Nowadays, knowledge is considered a key resource for organizations, crucial for obtaining long-term sustainable competitive. In line with this principle, many organizations are making efforts toward the implementation of knowledge management (KM) initiatives, recognizing that their competitive foundation lies in the effective way to capture, retain, store and share knowledge. Thus, this research aims to understand how organizations can implement KM initiatives, with a comprehensive study to identify critical success factors, and based on a practical project to implement a knowledge academy in a multinational organization. In order to achieve this objective, the adopted methodology in this research first went through a systematic literature review in order to identify the critical success factors with most influence on the implementation of KM practices. Then, based on the results found with this theoretical approach, it was possible to identify and analyse, in a practical context within a multinational company, the critical factors that contributed the most to the success of a knowledge academy implementation, a project in which the author of this study was involved. The results found suggest that factors related to the organization and people, such as the definition of a clear strategy, the definition of performance measures to evaluate and monitor the strategy, the involvement of top management, or even the organizational culture itself, represent some of the factors that have the most influence on the successful implementation of KM initiatives. With this research, it is expected to contribute from a theoretical perspective to the KM area through the compilation, categorization and classification of a set of critical success factors reported in the literature and subsequently analyzed and validated in a practical context. From a practical perspective, it is expected that these results can contribute as a consultative tool to support the preparation of strategies in this area by organizations wishing to implement KM initiatives.Atualmente o conhecimento é considerado um recurso chave para as organizações, crucial na obtenção de competitividade sustentável a longo prazo. Alinhado com este princípio, muitas organizações estão a fazer esforços no sentido de implementarem iniciativas de gestão do conhecimento (GC), reconhecendo que a sua base competitiva reside na forma eficaz de captar, reter, armazenar e partilhar conhecimento. Desta forma, o presente trabalho tem por objetivo compreender como as organizações podem implementar iniciativas de GC, elencando num estudo exaustivo de identificação de fatores críticos de sucesso, e tendo por base um projeto prático de implementação de uma academia de conhecimento numa organização multinacional. Por forma a alcançar tal objetivo, a metodologia adotada neste trabalho compreendeu, em primeiro lugar, uma revisão sistemática da literatura, de forma a identificar os fatores críticos de sucesso que mais influência têm na implementação de práticas de GC. Seguidamente, e tendo por base os resultados encontrados com esta abordagem teórica, foi possível identificar e analisar, num contexto prático no âmbito de uma empresa multinacional, os fatores críticos que mais contribuíram para o sucesso da implementação de uma academia de conhecimento, projeto onde a autora deste trabalho esteve envolvida. Os resultados encontrados sugerem que fatores relacionados com a organização e com as pessoas, tais como, a definição de uma estratégia clara, a definição de medidas de performance para avaliar e acompanhar a estratégia, o envolvimento da gestão de topo, ou mesmo a própria cultura organizacional, representam alguns dos fatores que mais influência têm na implementação bemsucedida de práticas e iniciativas de GC. Espera-se, assim, com este estudo, contribuir numa perspetiva teórica para a área da GC através da compilação, categorização e classificação de um conjunto de fatores críticos de sucesso reportados na literatura e, posteriormente, analisados e validados num contexto prático. Numa perspetiva prática, espera-se que estes resultados possam contribuir com uma ferramenta consultiva de apoio à preparação de estratégias nesta área, por parte das organizações que pretendam implementar iniciativas de GC.Mestrado em Engenharia e Gestão Industria

The Development of Digital Forensics Workforce Competency on the Example of Estonian Defence League

03.07.2014 kehtestati Vabariigi Valitsuse määrus nr. 108, mis reguleerib Kaitseliidu kaasamise tingimusi ja korda küberjulgeoleku tagamisel. Seega võivad Kaitseliidu küberkaitse üksuse (KL KKÜ edaspidi KKÜ) kutsuda olukorda toetama erinevad asutused: näiteks Riigi Infosüsteemide amet (RIA), infosüsteemi järelevalveasutus või kaitseministeerium või selle valitsemisala ametiasutused oma ülesannete raames. KKÜ-d saab kaasata info- ja sidetehnoloogia infrastruktuuri järjepidevuse tagamisel, turvaintsidentide kontrollimisel ja lahendamisel, rakendades nii aktiivseid kui passiivseid meetmeid. KKÜ ülesannete kaardistamisel täheldati, et KKÜ partnerasutused / organisatsioonid ei ole kaardistanud oma spetsialistide olemasolevaid pädevusi ja sellele lisaks puudub ülevaade digitaalse ekspertiisi kogukonnas vajaolevatest pädevustest. Leitut arvesse võttes seati ülesandeks vajadustest ja piirangutest (võttes arvesse digitaalse ekspertiisi kogukonda kujundavaid standardeid) ülevaatliku pildi loomine, et töötada välja digitaalse ekspertiisi kompetentsipõhine raamistik, mis toetab KKÜ spetsialistide arendamist palkamisest pensionini. Selleks uurisime KKÜ ja nende olemasolevate koolitusprogrammide hetkeolukorda ning otsustasime milliseid omadusi peab edasise arengu tarbeks uurima ja kaaluma. Võrreldavate tulemuste saa-miseks ja eesmärgi täitmiseks pidi koostatav mudel olema suuteline lahendama 5-t järgnevat ülesannet: 1. Oskuste kaardistamine, 2. Eesmärkide seadmine ja ümberhindamine, 3. Koolituskava planeerimine, 4. Värbamisprotsessi kiirendamine ning 5. Spetsialistide kestva arengu soodustamine. Raamistiku väljatöötamiseks võeti aluseks National Initiative for Cybersecurity Education (NICE) Cybersecurity Workforce Framework (NICE Framework) pädevusraamistik mida parendati digitaalse ekspertiisi spetsialistide, ja käesoleval juhul ka KKÜ, vajadusi silmas pidades. Täiendusi lisati nii tasemete, spetsialiseerumise kui ka ülesannete kirjelduste kujul. Parenduste lisamisel võeti arvesse töös tutvustatud digitaalse ekspertiisi piiranguid ja standardeid, mille lõpptulemusena esitati KKÜ-le Digitaalse Ekspertiisi Pädevuse ontoloogia, KKÜ struktuuri muudatuse ettepanek, soovitatavad õpetamisstrateegiad digitaalse ekspertiisi kasutamiseks (muudetud Bloomi taksonoomia tasemetega), uus digitaalse ekspertiisi standardi alajaotus – Mehitamata Süsteemide ekspertiis ja Digitaalse Ekspertiisi Pädevuse Mudeli Raamistik. Ülesannete ja oskuste loetelu koostati rahvusvaheliselt tunnustatud sertifitseerimis-organisatsioonide ja erialast pädevust pakkuvate õppekavade abil. Kavandatava mudeli hindamiseks kasutati mini-Delphi ehk Estimate-Talk-Estimate (ETE) tehnikat. Esialgne prognoos vajaduste ja prioriteetidega anti KKÜ partnerasutustele saamaks tehtud töö kohta ekspertarvamusi. Kogu tagasisidet silmas pidades tehti mudelisse korrektuurid ja KKÜ-le sai vormistatud ettepanek ühes edasise tööplaaniga. Üldiselt kirjeldab väljapakutud pädevusraamistik KKÜ spetsialistilt ooda-tavat pädevuse ulatust KKÜ-s, et suurendada nende rolli kiirreageerimisrühmana. Raamistik aitab määratleda digitaalse ekspertiisi eeldatavaid pädevusi ja võimekusi praktikas ning juhendab eksperte spetsialiseerumise valikul. Kavandatud mudeli juures on arvestatud pikaajalise mõjuga (palkamisest pensionini). Tulenevalt mudeli komplekssusest, on raamistikul pikk rakendusfaas – organisatsiooni arengule maksimaalse mõju saavutamiseks on prognoositud ajakava maksimaalselt 5 aastat. Antud ettepanekud on käesolevaks hetkeks KKÜ poolt heaks kiidetud ning planeeritud kava rakendati esmakordselt 2019 aasta aprillikuus.In 03.07.2014 Regulation No. 108 was introduced which regulates the conditions and pro-cedure of the involvement of the Estonian Defence League (EDL) Cyber Defence Unit (CDU) in ensuring cyber security. This means that EDL can be brought in by the Information System Authority, Ministry of Defence or the authorities of its area of government within the scope of either of their tasks e.g. ensuring the continuity of information and communication technology infrastructure and in handling and solving cyber security incidents while applying both active and passive measures. In January 2018 EDL CDU’s Digi-tal Evidence Handling Group had to be re-organized and, thus, presented a proposal for internal curriculum in order to further instruct Digital Evidence specialists. While describing the CDU's tasks, it was noted that the CDU's partner institutions / organizations have not mapped out their specialists’ current competencies. With this in mind, we set out to create a comprehensive list of needs and constraints (taking into account the community standards of DF) to develop a DF-based competence framework that supports the devel-opment of CDU professionals. Hence, we studied the current situation of CDU, their existing training program, and contemplated which features we need to consider and ex-plore for further development. In order to assemble comparable results and to achieve the goal the model had to be able to solve the 5 following tasks: 1. Competency mapping, 2. Goal setting and reassessment, 3. Scheduling the training plan, 4. Accelerating the recruitment process, and 5. Promoting the continuous development of professionals. The frame-work was developed on the basis of the National Initiative for Cybersecurity Education (NICE) Cybersecurity Workforce Framework (NICE Framework), which was revised to meet the needs of DF specialists, including EDL CDU. Additions were supplemented in terms of levels, specialization, and job descriptions. The proposals included the DF limitations and standards introduced in the work, which ultimately resulted in a proposal for a Digital Forensics Competency ontology, EDL CDU structure change, Suggested Instruc-tional Strategies for Digital Forensics Use With Each Level of revised Bloom's Taxonomy, a new DF standard subdivision – Unmanned Systems Forensics, and Digital Forensic Competency Model Framework. The list of tasks and skills were compiled from international certification distribution organizations and curricula, and their focus on DF Special-ist Competencies. Mini-Delphi or Estimate-Talk-Estimate (ETE) techniques were applied to evaluate the proposed model. An initial estimation of competencies and priorities were given to the EDL CDU partner institutions for expert advice and evaluation. Considering the feedback, improvements were made to the model and a proposal was put forward to the CDU with a future work plan. In general, the proposed competence framework describes the expected scope of competence of an DF specialist in the EDL CDU to enhance their role as a rapid response team. The framework helps in defining the expected compe-tencies and capabilities of digital forensics in practice and offers guidance to the experts in the choice of specialization. The proposed model takes into account the long-term effect (hire-to-retire). Due to the complexity of the model, the framework has a long implementation phase — the maximum time frame for achieving the full effect for the organization is expected to be 5 years. These proposals were approved by EDL CDU and the proposed plan was first launched in April 2019

Exploratory search in time-oriented primary data

In a variety of research fields, primary data that describes scientific phenomena in an original condition is obtained. Time-oriented primary data, in particular, is an indispensable data type, derived from complex measurements depending on time. Today, time-oriented primary data is collected at rates that exceed the domain experts’ abilities to seek valuable information undiscovered in the data. It is widely accepted that the magnitudes of uninvestigated data will disclose tremendous knowledge in data-driven research, provided that domain experts are able to gain insight into the data. Domain experts involved in data-driven research urgently require analytical capabilities. In scientific practice, predominant activities are the generation and validation of hypotheses. In analytical terms, these activities are often expressed in confirmatory and exploratory data analysis. Ideally, analytical support would combine the strengths of both types of activities. Exploratory search (ES) is a concept that seamlessly includes information-seeking behaviors ranging from search to exploration. ES supports domain experts in both gaining an understanding of huge and potentially unknown data collections and the drill-down to relevant subsets, e.g., to validate hypotheses. As such, ES combines predominant tasks of domain experts applied to data-driven research. For the design of useful and usable ES systems (ESS), data scientists have to incorporate different sources of knowledge and technology. Of particular importance is the state-of-the-art in interactive data visualization and data analysis. Research in these factors is at heart of Information Visualization (IV) and Visual Analytics (VA). Approaches in IV and VA provide meaningful visualization and interaction designs, allowing domain experts to perform the information-seeking process in an effective and efficient way. Today, bestpractice ESS almost exclusively exist for textual data content, e.g., put into practice in digital libraries to facilitate the reuse of digital documents. For time-oriented primary data, ES mainly remains at a theoretical state. Motivation and Problem Statement. This thesis is motivated by two main assumptions. First, we expect that ES will have a tremendous impact on data-driven research for many research fields. In this thesis, we focus on time-oriented primary data, as a complex and important data type for data-driven research. Second, we assume that research conducted to IV and VA will particularly facilitate ES. For time-oriented primary data, however, novel concepts and techniques are required that enhance the design and the application of ESS. In particular, we observe a lack of methodological research in ESS for time-oriented primary data. In addition, the size, the complexity, and the quality of time-oriented primary data hampers the content-based access, as well as the design of visual interfaces for gaining an overview of the data content. Furthermore, the question arises how ESS can incorporate techniques for seeking relations between data content and metadata to foster data-driven research. Overarching challenges for data scientists are to create usable and useful designs, urgently requiring the involvement of the targeted user group and support techniques for choosing meaningful algorithmic models and model parameters. Throughout this thesis, we will resolve these challenges from conceptual, technical, and systemic perspectives. In turn, domain experts can benefit from novel ESS as a powerful analytical support to conduct data-driven research. Concepts for Exploratory Search Systems (Chapter 3). We postulate concepts for the ES in time-oriented primary data. Based on a survey of analysis tasks supported in IV and VA research, we present a comprehensive selection of tasks and techniques relevant for search and exploration activities. The assembly guides data scientists in the choice of meaningful techniques presented in IV and VA. Furthermore, we present a reference workflow for the design and the application of ESS for time-oriented primary data. The workflow divides the data processing and transformation process into four steps, and thus divides the complexity of the design space into manageable parts. In addition, the reference workflow describes how users can be involved in the design. The reference workflow is the framework for the technical contributions of this thesis. Visual-Interactive Preprocessing of Time-Oriented Primary Data (Chapter 4). We present a visual-interactive system that enables users to construct workflows for preprocessing time-oriented primary data. In this way, we introduce a means of providing content-based access. Based on a rich set of preprocessing routines, users can create individual solutions for data cleansing, normalization, segmentation, and other preprocessing tasks. In addition, the system supports the definition of time series descriptors and time series distance measures. Guidance concepts support users in assessing the workflow generalizability, which is important for large data sets. The execution of the workflows transforms time-oriented primary data into feature vectors, which can subsequently be used for downstream search and exploration techniques. We demonstrate the applicability of the system in usage scenarios and case studies. Content-Based Overviews (Chapter 5). We introduce novel guidelines and techniques for the design of contentbased overviews. The three key factors are the creation of meaningful data aggregates, the visual mapping of these aggregates into the visual space, and the view transformation providing layouts of these aggregates in the display space. For each of these steps, we characterize important visualization and interaction design parameters allowing the involvement of users. We introduce guidelines supporting data scientists in choosing meaningful solutions. In addition, we present novel visual-interactive quality assessment techniques enhancing the choice of algorithmic model and model parameters. Finally, we present visual interfaces enabling users to formulate visual queries of the time-oriented data content. In this way, we provide means of combining content-based exploration with content-based search. Relation Seeking Between Data Content and Metadata (Chapter 6). We present novel visual interfaces enabling domain experts to seek relations between data content and metadata. These interfaces can be integrated into ESS to bridge analytical gaps between the data content and attached metadata. In three different approaches, we focus on different types of relations and define algorithmic support to guide users towards most interesting relations. Furthermore, each of the three approaches comprises individual visualization and interaction designs, enabling users to explore both the data and the relations in an efficient and effective way. We demonstrate the applicability of our interfaces with usage scenarios, each conducted together with domain experts. The results confirm that our techniques are beneficial for seeking relations between data content and metadata, particularly for data-centered research. Case Studies - Exploratory Search Systems (Chapter 7). In two case studies, we put our concepts and techniques into practice. We present two ESS constructed in design studies with real users, and real ES tasks, and real timeoriented primary data collections. The web-based VisInfo ESS is a digital library system facilitating the visual access to time-oriented primary data content. A content-based overview enables users to explore large collections of time series measurements and serves as a baseline for content-based queries by example. In addition, VisInfo provides a visual interface for querying time oriented data content by sketch. A result visualization combines different views of the data content and metadata with faceted search functionality. The MotionExplorer ESS supports domain experts in human motion analysis. Two content-based overviews enhance the exploration of large collections of human motion capture data from two perspectives. MotionExplorer provides a search interface, allowing domain experts to query human motion sequences by example. Retrieval results are depicted in a visual-interactive view enabling the exploration of variations of human motions. Field study evaluations performed for both ESS confirm the applicability of the systems in the environment of the involved user groups. The systems yield a significant improvement of both the effectiveness and the efficiency in the day-to-day work of the domain experts. As such, both ESS demonstrate how large collections of time-oriented primary data can be reused to enhance data-centered research. In essence, our contributions cover the entire time series analysis process starting from accessing raw time-oriented primary data, processing and transforming time series data, to visual-interactive analysis of time series. We present visual search interfaces providing content-based access to time-oriented primary data. In a series of novel explorationsupport techniques, we facilitate both gaining an overview of large and complex time-oriented primary data collections and seeking relations between data content and metadata. Throughout this thesis, we introduce VA as a means of designing effective and efficient visual-interactive systems. Our VA techniques empower data scientists to choose appropriate models and model parameters, as well as to involve users in the design. With both principles, we support the design of usable and useful interfaces which can be included into ESS. In this way, our contributions bridge the gap between search systems requiring exploration support and exploratory data analysis systems requiring visual querying capability. In the ESS presented in two case studies, we prove that our techniques and systems support data-driven research in an efficient and effective way

Ettevõtete innovatsioonistrateegiate dünaamika ja seosed avaliku sektori toetustega

Innovatsiooni peetakse õigustatult majandusarengu võtmeks. Innovaatilisuse suurendamiseks toetatakse eraettevõtlust riikliku abiga, millest tulenevalt tekib küsimus – kas toetused tõepoolest muudavad ettevõtete käitumist? Doktoritöö keskendub ettevõtete innovatsioonistrateegiate dünaamikale ning seostele ettevõtlustoetustega. Viimased võivad olla näiteks investeeringute tegemiseks, teadus- ja arendustegevuseks, innovatsioonide turule toomiseks, turundusplaanideks, jne. Eesti näitel on hinnatud ettevõtete innovatsioonistrateegiaid, mis toetuvad ühistele sisenditele. Olgu selleks koostööpartnerite valik, valikud investeeringute tegemisel või teadmiste allikad. Selgub, et ettevõtted on võimelised oma innovatsioonistrateegiat muutma tihti, vajadusel mõne aasta jooksul. Siiski on tegemist astmelise arenguga, kõigepealt tulevad lihtsamad strateegiad ja alles seejärel keerulisemad. Seosed ettevõtlustoetustega ei ole ühtsed. Näiteks investeeringutoetustega ettevõtted võtavad suurema tõenäosusega kasutusele lihtsamad innovatsioonistrateegiad. Teadus- ja arendustegevusele suunatud toetustega ettevõtted aga juba keerulisemad strateegiad. Töötajate oskuste arendamisele suunatud toetustega ettevõtted püsivad kauem innovaatilised. Siiski on mitmed toetuste tüübid, kus pole selge, et nad üldse oleks seotud innovatsioonistrateegiatega. Doktoritööst ilmneb, et ettevõtlustoetused peaksid olema disainitud täpsemaid tegevuspõhiseid sihtgruppe silmas pidades. Innovatsioonistrateegiates ei tasu oodata suuri hüppeid vaid järkjärgulist arengut. Kuid oma sihtgrupis peaksid nad olema piisavalt väljakutsuvad, et toetada strateegiaid mis on kogu majandusele kasulikud – avatud, koostööaltid ja teadmuspõhised.Innovation has been on the forefront of public policy as a panacea for economic ills for a long time. Governments on various levels support the creation and diffusion of innovations in private firms with public money. It is justified to ask – does it change firm behaviour? The thesis analyses whether firms change their innovation strategies if they have received business support. The support can be in various forms, such as financial aid to investments, training and skill development, developing marketing plans and exporting plans, innovation and R&D assistance, and so forth. Based on the Estonian example, some commonalities can be established about innovation strategies. Firms adopt different styles of creating innovations relying on diverse inputs, such as their cooperation partners, investment choices or information sources. Firms change between different strategies often and with a short time-frame, in less than two years. Meaning that with proper incentives, it is possible to influence firm behaviour without long lags. However, shifts between strategies show incremental evolution. Firms without any innovation strategies develop simple strategies first, followed by more complex strategies later. The relationship with business support is not uniform. Support for physical capital investments is positively related with simple innovation strategies. Support for innovation and R&D activities is more related with complex innovation strategies, based on open innovation strategies and cooperation with universities. Firms with training and skill development instruments are less likely to stop being innovative at all. Business support should adapt to the proper target audience. Leap-frogging might have limits if firms are very inexperienced. In addition, policy instruments ought to be demanding for firms. Innovation policy instruments should be challenging enough to create strategies that we wish to promote — cooperative, open and R&D intensive.https://www.ester.ee/record=b530632

Strategies for sustainable socio-economic development and mechanisms their implementation in the global dimension

The authors of the book have come to the conclusion that it is necessary to effectively use modern approaches to developing and implementation strategies of sustainable socio-economic development in order to increase efficiency and competitiveness of economic entities. Basic research focuses on economic diagnostics of socio-economic potential and financial results of economic entities, transition period in the economy of individual countries and ensuring their competitiveness, assessment of educational processes and knowledge management. The research results have been implemented in the different models and strategies of supply and logistics management, development of non-profit organizations, competitiveness of tourism and transport, financing strategies for small and medium-sized enterprises, cross-border cooperation. The results of the study can be used in decision-making at the level the economic entities in different areas of activity and organizational-legal forms of ownership, ministries and departments that promote of development the economic entities on the basis of models and strategies for sustainable socio-economic development. The results can also be used by students and young scientists in modern concepts and mechanisms for management of sustainable socio-economic development of economic entities in the condition of global economic transformations and challenges